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Liu YH, Liu TT, Niu JQ, Zhang XS, Xu WS, Song S, Wang Z. Characterization of phospholipidome in milk, yogurt and cream, and phospholipid differences related to various dairy processing methods. Food Chem 2024; 454:139733. [PMID: 38805923 DOI: 10.1016/j.foodchem.2024.139733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/27/2024] [Accepted: 05/16/2024] [Indexed: 05/30/2024]
Abstract
Milk phospholipids have multiple health benefits, but the deficiency of detailed phospholipid profiles in dairy products brings obstacles to intake calculation and function evaluation of dairy phospholipids. In present study, 306 phospholipid molecular species were identified and quantified among 207 milk, yogurt and cream products using a HILIC-ESI-Q-TOF MS and a HILIC-ESI-QQQ MS. The phospholipid profiles of five mammals' milk show that camel milk contains the most abundant phosphatidylethanolamine, phosphatidylserine and sphingomyelin; cow, yak and goat milk have similar phospholipidomes, while buffalo milk contains abundant phosphatidylinositol. Fewer plasmalogens but more lyso-glycerolphospholipids were found in ultra-high-temperature (UHT) sterilized milk than in pasteurized milk, and higher proportions of lyso-glycerolphospholipid/total phospholipid were observed in both cream and skimmed/semi-skimmed milk than whole milk, indicating that UHT and skimming processes improve glycerolphospholipid degradation and phospholipid nutrition loss. Meanwhile, more diacyl-glycerolphospholipids and less of their degradation products make yogurt a better phospholipid resource than whole milk.
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Affiliation(s)
- Yue-Han Liu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Ting-Ting Liu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Jing-Qi Niu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Xue-Song Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Wei-Sheng Xu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Shuang Song
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China; Key Laboratory of Public Nutrition and Health, National Health Commission of the People's Republic of China, Beijing 100000, China.
| | - Zhu Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
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2
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Calderón-Pérez L, Escoté X, Companys J, Alcaide-Hidalgo JM, Bosch M, Rabassa M, Crescenti A, Valls RM, Pedret A, Solà R, Mariné R, Gil-Cardoso K, Rodríguez MA, Palacios H, Del Pino A, Guirro M, Canela N, Suñol D, Galofré M, Galmés S, Palou-March A, Serra F, Caimari A, Gutiérrez B, Del Bas JM. A single-blinded, randomized, parallel intervention to evaluate genetics and omics-based personalized nutrition in general population via an e-commerce tool: The PREVENTOMICS e-commerce study. Am J Clin Nutr 2024; 120:129-144. [PMID: 38960570 DOI: 10.1016/j.ajcnut.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 03/04/2024] [Accepted: 04/02/2024] [Indexed: 07/05/2024] Open
Abstract
BACKGROUND Personalized nutrition (PN) has been proposed as a strategy to increase the effectiveness of dietary recommendations and ultimately improve health status. OBJECTIVES We aimed to assess whether including omics-based PN in an e-commerce tool improves dietary behavior and metabolic profile in general population. METHODS A 21-wk parallel, single-blinded, randomized intervention involved 193 adults assigned to a control group following Mediterranean diet recommendations (n = 57, completers = 36), PN (n = 70, completers = 45), or personalized plan (PP, n = 68, completers = 53) integrating a behavioral change program with PN recommendations. The intervention used metabolomics, proteomics, and genetic data to assist participants in creating personalized shopping lists in a simulated e-commerce retailer portal. The primary outcome was the Mediterranean diet adherence screener (MEDAS) score; secondary outcomes included biometric and metabolic markers and dietary habits. RESULTS Volunteers were categorized with a scoring system based on biomarkers of lipid, carbohydrate metabolism, inflammation, oxidative stress, and microbiota, and dietary recommendations delivered accordingly in the PN and PP groups. The intervention significantly increased MEDAS scores in all volunteers (control-3 points; 95% confidence interval [CI]: 2.2, 3.8; PN-2.7 points; 95% CI: 2.0, 3.3; and PP-2.8 points; 95% CI: 2.1, 3.4; q < 0.001). No significant differences were observed in dietary habits or health parameters between PN and control groups after adjustment for multiple comparisons. Nevertheless, personalized recommendations significantly (false discovery rate < 0.05) and selectively enhanced the scores calculated with biomarkers of carbohydrate metabolism (β: -0.37; 95% CI: -0.56, -0.18), oxidative stress (β: -0.37; 95% CI: -0.60, -0.15), microbiota (β: -0.38; 95% CI: -0.63, -0.15), and inflammation (β: -0.78; 95% CI: -1.24, -0.31) compared with control diet. CONCLUSIONS Integration of personalized strategies within an e-commerce-like tool did not enhance adherence to Mediterranean diet or improved health markers compared with general recommendations. The metabotyping approach showed promising results and more research is guaranteed to further promote its application in PN. This trial was registered at clinicaltrials.gov as NCT04641559 (https://clinicaltrials.gov/study/NCT04641559?cond=NCT04641559&rank=1).
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Affiliation(s)
| | - Xavier Escoté
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, Spain
| | - Judit Companys
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, Spain
| | | | - Mireia Bosch
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, Spain
| | - Montserrat Rabassa
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, Spain; Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Nutrition and Food Safety Research Institute (INSA), Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona (UB), Barcelona, Spain
| | - Anna Crescenti
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, Spain
| | - Rosa M Valls
- Functional Nutrition, Oxidation and Cardiovascular Diseases Group (NFOC-Salut), Facultat de Medicina i Ciències de la Salut, Universitat Rovira i Virgili, Reus, Spain
| | - Anna Pedret
- Functional Nutrition, Oxidation and Cardiovascular Diseases Group (NFOC-Salut), Facultat de Medicina i Ciències de la Salut, Universitat Rovira i Virgili, Reus, Spain
| | - Rosa Solà
- Functional Nutrition, Oxidation and Cardiovascular Diseases Group (NFOC-Salut), Facultat de Medicina i Ciències de la Salut, Universitat Rovira i Virgili, Reus, Spain; Internal Medicine Service, Hospital Universitari Sant Joan de Reus, Reus, Spain
| | - Roger Mariné
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, Reus, Spain
| | | | - Miguel A Rodríguez
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Reus, Spain
| | - Héctor Palacios
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Reus, Spain
| | - Antoni Del Pino
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Reus, Spain
| | - María Guirro
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Reus, Spain
| | - Núria Canela
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Reus, Spain
| | - David Suñol
- Eurecat, Centre Tecnològic de Catalunya, Digital Health, Barcelona, Spain
| | - Mar Galofré
- Eurecat, Centre Tecnològic de Catalunya, Digital Health, Barcelona, Spain
| | - Sebastià Galmés
- Laboratory of Molecular Biology, Nutrition and Biotechnology (Group of Nutrigenomics, Biomarkers and Risk Evaluation - NuBE), University of the Balearic Islands, Palma, Spain; Health Research Institute of the Balearic Islands (IdISBa), Palma, Spain; Centro de investigación Biomédica en red de Fisiopatología de la obesidad y nutrición, Instituto de Salud Carlos III, Madrid, Spain; Alimentómica S.L. Camí de na Pontons, Campanet, Spain
| | - Andreu Palou-March
- Laboratory of Molecular Biology, Nutrition and Biotechnology (Group of Nutrigenomics, Biomarkers and Risk Evaluation - NuBE), University of the Balearic Islands, Palma, Spain; Health Research Institute of the Balearic Islands (IdISBa), Palma, Spain; Centro de investigación Biomédica en red de Fisiopatología de la obesidad y nutrición, Instituto de Salud Carlos III, Madrid, Spain; Alimentómica S.L. Camí de na Pontons, Campanet, Spain
| | - Francisca Serra
- Laboratory of Molecular Biology, Nutrition and Biotechnology (Group of Nutrigenomics, Biomarkers and Risk Evaluation - NuBE), University of the Balearic Islands, Palma, Spain; Health Research Institute of the Balearic Islands (IdISBa), Palma, Spain; Centro de investigación Biomédica en red de Fisiopatología de la obesidad y nutrición, Instituto de Salud Carlos III, Madrid, Spain; Alimentómica S.L. Camí de na Pontons, Campanet, Spain
| | - Antoni Caimari
- Eurecat, Centre Tecnològic de Catalunya, Biotechnology Area, Reus, Spain
| | - Biotza Gutiérrez
- Eurecat, Centre Tecnològic de Catalunya, Biotechnology Area, Reus, Spain
| | - Josep M Del Bas
- Eurecat, Centre Tecnològic de Catalunya, Biotechnology Area, Reus, Spain.
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Kortesniemi M, Noerman S, Kårlund A, Raita J, Meuronen T, Koistinen V, Landberg R, Hanhineva K. Nutritional metabolomics: Recent developments and future needs. Curr Opin Chem Biol 2023; 77:102400. [PMID: 37804582 DOI: 10.1016/j.cbpa.2023.102400] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 08/21/2023] [Accepted: 09/07/2023] [Indexed: 10/09/2023]
Abstract
Metabolomics has rapidly been adopted as one of the key methods in nutrition research. This review focuses on the recent developments and updates in the field, including the analytical methodologies that encompass improved instrument sensitivity, sampling techniques and data integration (multiomics). Metabolomics has advanced the discovery and validation of dietary biomarkers and their implementation in health research. Metabolomics has come to play an important role in the understanding of the role of small molecules resulting from the diet-microbiota interactions when gut microbiota research has shifted towards improving the understanding of the activity and functionality of gut microbiota rather than composition alone. Currently, metabolomics plays an emerging role in precision nutrition and the recent developments therein are discussed.
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Affiliation(s)
- Maaria Kortesniemi
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland.
| | - Stefania Noerman
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
| | - Anna Kårlund
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland
| | - Jasmin Raita
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland
| | - Topi Meuronen
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland
| | - Ville Koistinen
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland; Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, FI-70211 Kuopio, Finland
| | - Rikard Landberg
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
| | - Kati Hanhineva
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland; Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, FI-70211 Kuopio, Finland
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Näätänen M, Kårlund A, Mikkonen S, Klåvus A, Savolainen O, Lehtonen M, Karhunen L, Hanhineva K, Kolehmainen M. Metabolic profiles reflect weight loss maintenance and the composition of diet after very-low-energy diet. Clin Nutr 2023; 42:1126-1141. [PMID: 37268538 DOI: 10.1016/j.clnu.2023.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 05/08/2023] [Accepted: 05/12/2023] [Indexed: 06/04/2023]
Abstract
BACKGROUND & AIMS Diet and weight loss affect circulating metabolome. However, metabolite profiles induced by different weight loss maintenance diets and underlying longer term weight loss maintenance remain unknown. Herein, we investigated after-weight-loss metabolic signatures of two isocaloric 24-wk weight maintenance diets differing in satiety value due to dietary fibre, protein and fat contents and identified metabolite features that associated with successful weight loss maintenance. METHODS Non-targeted LC-MS metabolomics approach was used to analyse plasma metabolites of 79 women and men (mean age ± SD 49.7 ± 9.0 years; BMI 34.2 ± 2.5 kg/m2) participating in a weight management study. Participants underwent a 7-week very-low-energy diet (VLED) and were thereafter randomised into two groups for a 24-week weight maintenance phase. Higher satiety food (HSF) group consumed high-fibre, high-protein, and low-fat products, while lower satiety food (LSF) group consumed isocaloric low-fibre products with average protein and fat content as a part of their weight maintenance diets. Plasma metabolites were analysed before the VLED and before and after the weight maintenance phase. Metabolite features discriminating HSF and LSF groups were annotated. We also analysed metabolite features that discriminated participants who maintained ≥10% weight loss (HWM) and participants who maintained <10% weight loss (LWM) at the end of the study, irrespective of the diet. Finally, we assessed robust linear regression between metabolite features and anthropometric and food group variables. RESULTS We annotated 126 metabolites that discriminated the HSF and LSF groups and HWM and LWM groups (p < 0.05). Compared to LSF, the HSF group had lower levels of several amino acids, e.g. glutamine, arginine, and glycine, short-, medium- and long-chain acylcarnitines (CARs), odd- and even-chain lysoglycerophospholipids, and higher levels of fatty amides. Compared to LWM, the HWM group in general showed higher levels of glycerophospholipids with a saturated long-chain and a C20:4 fatty acid tail, and unsaturated free fatty acids (FFAs). Changes in several saturated odd- and even-chain LPCs and LPEs and fatty amides were associated with the intake of many food groups, particularly grain and dairy products. Increase in several (lyso)glycerophospholipids was associated with decrease in body weight and adiposity. Increased short- and medium-chain CARs were related to decreased body fat-free mass. CONCLUSIONS Our results show that isocaloric weight maintenance diets differing in dietary fibre, protein, and fat content affected amino acid and lipid metabolism. Increased abundances of several phospholipid species and FFAs were related with greater weight loss maintenance. Our findings indicate common and distinct metabolites for weight and dietary related variables in the context of weight reduction and weight management. The study was registered in isrctn.org with identifier 67529475.
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Affiliation(s)
- Mari Näätänen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Anna Kårlund
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Department of Life Technologies, Food Sciences Unit, University of Turku, 20014 Turku, Finland.
| | - Santtu Mikkonen
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Anton Klåvus
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Otto Savolainen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Department of Biology and Biological Engineering, Chalmers Mass Spectrometry Infrastructure, Chalmers University of Technology, Sweden.
| | - Marko Lehtonen
- School of Pharmacy, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Leila Karhunen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Kati Hanhineva
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Department of Life Technologies, Food Sciences Unit, University of Turku, 20014 Turku, Finland.
| | - Marjukka Kolehmainen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
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